Monthly Archives: March 2014

The meta-answer here I feel is that with each answer to this question comes backed behind it a new direction to look at.

Let’s do some review. I’ve come to see the statistical output in 2 types: Averages, and Edges. Quite simply, it’s either there or it isn’t. The coin ends up on heads either more/less than 50% of the time, or about 50% of the time. Can you trade an average? I think so. Coins and cards obviously have no memory, but it’s not a jaw dropping idea that the market could.

Averages: These all end up yielding the same numbers

Chance that a bar will be red or green, depending on the bar behind it (50%)

Type of day following other types. Likelihood of an A wave following a B wave, etc. (same as independent)

Length/ratio of larger wave waves to their smaller waves (length of the B portion of the B wave compared to the A portion)

Length of the last portion of the wave (same length)

Edges:

Time of day extremes are created (Mid London/US)

Type of wave created (ABC)

Standard deviation of the range of a weekly wave(much smaller)

Days of the week extremes are created(Monday/Tuesday)

Excluded from these categories are statistics they may be useful, but their standard deviations are too big to be worth anything. That’s what I want to look at. I can say the A portion of a B wave is about 52 pips and the A portion of the C wave is about 35 pips, which is useful, but the standard deviations create a range of 15-89 pips for the B wave and 15 to 55 for the C wave. Thus I can be fairly sure that a wave is more likely to be an A or B wave after the wave length becomes over 55, but by then the wave is probably already over. Not useful anymore. Statistics like these aren’t really averages, they’re more like non-edges, and there’s a difference, especially if you believe that averages can be traded. And if you pay close attention to the statistics that have been coming out, this happens pretty often.

In creating a possible framework for how price behaves, there needs to be a balance between letting the data speak for itself and knowing what it’s probably for. I’ve probably spoken about this before but it really plays a factor. If I get an edge, it will show itself, brightly. but if I get a different result, what does this mean? It’s not as simple as saying that if an edge isn’t produced, than there’s no edge. Certain results create possibilities for further research on a more specified question.

Example:

Background: We know the average day’s length is about 60 pips, with a StDev of about 60 as well. We also know the average hour’s length is about 17, with a StDev of about 13.

Break it down:

It’s not enough to be happy that the average length is 17 pips with a 13 pip Stdev. Anytime the Stdev is about as big as the actual average, one has to realize that it hurts the usefulness of the average in the first place because it means I can DOUBLE the average and the result would still be in the realm of possibility and in fact, quite likely.

The REASON the standard deviation is large is because certain hours of the day are more active. We know this. But it requires foresight and active questioning to think of possible reasons if I did not possess that knowledge. “Why is the average bar have such a high Stdev? Maybe something will show if I look at each bar individually”.

However the harder questions cannot be answered by just zeroing in and isolating. It may be part of it, but the method used to isolate it becomes important.

Lets go further.

We now ‘know’ that the reason the StDev is large is because the dead zones in the market are as small as 10 to 20 pips, while the active hours can create 50 or 60 pips. This is obviously important because we want to trade the active hours. However, if I continue to be critical, it becomes apparent that yes, we’ve discovered something new and cool about the market, but the issue is still there! We’ve managed to cut down the StDevs by quite a bit, but we still have a lot of variety. There are two factors. One of the obvious factors is that the market is creating pips and ranges both up and down, but the second is more important, and less obvious…

What did I just say about the active hours? 50-60? Say.. that’s about the average range of a day! take one or two of those suckers and you don’t even need the rest of the hours to be contributing any pips at all! Wait that might actually be leading to something..

Current range. Daily “max”. Daily “move”. The reality is that once the days’ range is done, it’s done. If a day made a dip in the open and made a strong move during the U.S session, it’s not going to keep completing the numbers for the rest of the hours. We’re not likely to see 10 pip moves every hour until the day shuts down. We only see moves later if perhaps it didn’t occur earlier. In other words, more pips completed in 1 hour means less room for pips to be made in the next hour. I provided a small statistic that the average range from 20:00 to 23:00 is 30 pips, and we clearly see that the sum of the averages is about double. This is simply a phenomenon of the market.

If one were to think that every large StDev has an explanation then.. time to get workin.

I can’t recall how many times I’ve done this. I’m actually pretty okay with these results currently. I have a new direction (possibly) to be going in soon which will put these statistics in the back of my head but the actual waves on the back burner… There’s been an interesting.. deductive conclusion to all of these results I’ve been working on for the past couple months. Think Edison. It’s not necessarily about what works, it’s about what doesn’t work. What doesn’t work obviously isn’t as good, but it is something. Obviously can’t confirm until something IS found to prove my hypothesis which may or may not happen, but progress is key..

ABC accounting for 74% is not bad. Not bad at all.

As expected, the bigger the wave, the bigger the MM. Except for the E wave, which is a rare occasion anyway.

The following data is charted into 5 columns, each headed with 1 day of the week. Monday on the left, Friday on the right. The top row has only 1 day while every other row is a combination of two days. The data looks at directions of days compared to the week. For example in the top row, if Monday is up, then the week will be up 60.82 % of the time, and it will be down 39.18% of the time(also provided in previous statistic). If Monday AND Tuesday are up, the week will be up 76% of the time, and down 24% of the time. Tradeable? Perhaps, although keep in mind that if you’re using the Monday-Tuesday statistic, your chance my already be over by the end of Tuesday. Still some opportunity when combined with other things, but not stand alone

Might have done something similar to this before. But the message is pretty clear. This is some light proof that the weeks tend to average out a lot better than the other time frames by quite a bit. I even included the 4HR (a TF I think is fundamentally flawed yet a popular choice by many). All the time frames show standard deviations that are pretty close to their averages except for the weekly. I’m not quite sure what kind of number I was expecting for the deviation but 75 seems pretty good. An upper limit of about ~365 seems very reasonable.